In 2012, a new prenatal screening test stormed the market and has become one of the most quickly adopted medical tests in recent history. It goes by many names including cell-free DNA prenatal screening (cfDNA screening), Non-Invasive prenatal Testing or Screening (NIPT or NIPS), and many brand names (MaterniT21®, Harmony®, Panorama®, etc). It’s being hailed as a game changer for diagnosing genetic conditions in pregnancy, but as the test has been more widely used and the statistics more closely examined, it may not be living up to the initial hype. Let’s take a closer look at what is being touted as the most advanced blood screening test in history.

What are we testing for?

Every pregnancy is at risk of having a “chromosomal imbalance” or too much or too little genetic material. The vast majority of humans have 46 chromosomes. A baby gets half of their chromosomes from Mom, and the other half from Dad. But this process doesn’t always go according to plan and some babies end up with an extra or missing chromosome.

When this happens, it causes different conditions, depending on which chromosome is involved. The most common condition is Down syndrome, which is caused by an extra copy of chromosome #21 (they have 3 instead of two).

Chromosomes of someone with Down syndrome
The chromosomes of someone with Down syndrome


There are many other conditions that are possible as well, some more mild than Down syndrome, and some much more severe. These chromosomal imbalances can be diagnosed during pregnancy with an amniocentesis or CVS (chorionic villus sampling). These tests are widely available by many experienced providers, but they involve putting a needle in Mom’s belly, so most people aren’t super eager to sign up for one.

Traditional Screening

People tend to be more comfortable with needle in their arm than in their belly, so for decades, we have been using blood tests to try and determine which women are more likely to be carrying a baby with a chromosomal condition. The traditional methods are based on measuring the amounts of several normal pregnancy hormones in Mom’s blood and comparing them to other women. We’ve determined that women carrying babies with certain conditions or certain birth defects, tend to have recognizable patterns in these hormone levels. The more closely a woman’s hormone levels match those patterns, the higher the chance her baby has that condition. The results of the test could show a risk anywhere from as high as 1 in 3 (33.3%), to as low as 1 in 100,000, but they will never tell us for sure either way. There are many, many healthy babies who have hormone levels that mimic babies with certain conditions, and some babies with those conditions that are missed by the test because they don’t fit the expected patterns.

New Technology

The way cell-free DNA screening works is different from traditional screening. It turns out that when a woman is pregnant, tiny pieces of the placenta’s DNA end up in her blood stream. This DNA isn’t protected by a cell, it’s just floating freely (hence “cell-free”). This makes it very unstable. In fact, it’s completely gone within a few hours of giving birth. It’s not alone, though. Mom’s own DNA is floating by along side it.

The baby and placenta both came from the same fertilized egg, so they should have the same DNA (there are exceptions to this rule). With a tube of Mom’s blood, they can gather up all the free floating DNA and tally up how many pieces they have from each chromosome they’re concerned about. If they find more pieces than they were expecting, they’ll assume it’s because the baby has an extra copy of that chromosome, and they’ll report that result out as “positive” for that specific condition.

Tally marks next to chromosomes 13, 18 and 21
How NIPT works. Except the labs use a computer, I imagine…

Statistics (Bear with me)

The big question about this, or any screening test is, how accurate is it? Well, there’s more than one way to answer that question. If you look at the websites or brochures for some of these tests, you’ll see one number thrown around a lot: 99%. That’s the number that got the whole prenatal community (doctors, genetic counselors and patients included) all in a flutter over these tests. 99%? Sounds amazing! And technically, it’s true, but not in the way you might think. To understand, we’re going to have to dive into just a little bit of statistics. I’m a genetics nerd, not a math nerd, so I’ll try to keep this as painless as possible for both of us.

Sensitivity and Specificity

That 99% number I mentioned is usually referring to the sensitivity and specificity of the test. The sensitivity could also be called the detection rate, or how many cases the test “picks-up” out of the total cases. If you had 100 babies with Down syndrome, and the test correctly called 99 of them “positive,” that test would have a sensitivity of 99%. It doesn’t matter how many times it got it wrong. It could also call 100 babies without Down syndrome “positive” at the same time and still be called 99% sensitive.

The specificity is like the flip side of sensitivity. That’s the proportion of “negatives” the test got right. If there were 100 babies that didn’t have Down syndrome, and the test called 99 of them “negative,” the test would have a 99% specificity. It also doesn’t matter that it called some of the babies with Down syndrome “negative” too.

So what does this all mean?

Positive Predictive Value of a positive test for Down syndrome in a 20 year old woman ( credit: University of North Carolina at Chapel Hill PPV calculator)
Positive Predictive Value of a positive test for Down syndrome in a 20 year old woman ( credit: University of North Carolina at Chapel Hill PPV calculator)

As you might be gathering, sensitivity and specificity don’t mean much on their own. When someone gets a positive result on this test, they don’t want to know how many babies with Down syndrome are picked up by this test in general, they want to know what are the chances their baby really has it. What they really want to know is the true positive rate or “positive predictive value” (PPV). That’s the percentage of babies with positive results that really do have Down syndrome. In order to figure that out, you actually need to know how common the condition is. The chance to have a baby with these conditions increases as moms get older, so we can use mom’s age to figure out what her test’s PPV is if we know the specificity and sensitivity. Luckily, someone made some nifty calculators to do this for us (check them out here and here). Just by playing around with them, you can see that a positive result on one of these tests does NOT mean there’s a 99% chance the baby actually has the condition in question. In fact, if you’re in your early 20’s, depending on which brand is used, the chance your “positive” result for Down syndrome is right could be as low as 38%! And Down syndrome is the condition with the most accuracy. Get into the more rare conditions and you could be looking at PPV’s in the teens or single digits.

Don’t get me wrong, 38% is considered high risk; higher than even the highest risk traditional screening will give you. But it’s nowhere near the 99% most people hear about, and definitely not high enough to base any kind of medical decisions off of.

Now from what I’ve seen, the labs don’t put the PPV’s are on their results reports; they use pretty black and white language (positive/negative, detected/not detected, etc). Personally, I feel this is misleading and creates a lot of unnecessary anxiety for the moms having the tests. I think it’s going to be bad for the labs in the long run, too. As more of these tests are performed, more false positives are being found, and more women are taking to the internet to share their stories. If the 99% number keeps showing up in the lab’s marketing, and it doesn’t match what people have experienced, they’re going to end up loosing credibility. That would be a shame, since the tests are really good for what they are. They’re just not as amazing as some people have been lead to believe. I hope the labs decide to be more clear about their statistics and what their tests actually mean for the real people that have them, for everyone’s sake.

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